Skip to main content
SpringerLink
Log in

Enhancing the Quality of Open Data

  • Chapter
  • First Online:
The Philosophy of Information Quality

Part of the book series: Synthese Library ((SYLI,volume 358))

Abstract

This paper looks at some of the quality issues relating to open data. This is problematic because of an open-data specific paradox: most metrics of quality are user-relative, but open data are aimed at no specific user and are simply available online under an open licence, so there is no user to be relevant to. Nevertheless, it is argued that opening data to scrutiny can improve quality by building feedback into the data production process, although much depends on the context of publication. The paper discusses various heuristics for addressing quality, and also looks at institutional approaches. Furthermore, if the open data can be published in linkable or bookmarkable form using Semantic Web technologies, that will provide further mechanisms to improve quality.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alani, H., Hall, W., O’Hara, K., Shadbolt, N., Szomszor, M., & Chandler, P. (2008). Building a pragmatic semantic web. IEEE Intelligent Systems, 23(3), 61–68.

    Article  Google Scholar 

  • Ayres, I. (2007). Super crunchers: How anything can be predicted. London: John Murray.

    Google Scholar 

  • Bennett D., & Harvey, A. (2009). Publishing open government data. World Wide Web Consortium. http://www.w3.org/TR/gov-data/

  • Berners-Lee, T. (2010). Linked data. World Wide Web Consortium. http://www.w3.org/DesignIssues/LinkedData.html

  • Gil, Y., et al. (2012). PROV model primer. World Wide Web Consortium. http://www.w3.org/TR/prov-primer/

  • Hayek, F. A. (1945). The use of knowledge in society. American Economic Review, 35(4), 519–530.

    Google Scholar 

  • Hendler, J., Holm, J., Musialek, C., & Thomas, G. (2012). US government linked open data: semantic.data.gov. IEEE Intelligent Systems, 27(3), 25–31.

    Article  Google Scholar 

  • Information Commissioner’s Office. (2010). Crime mapping and geo-spatial crime data: Privacy and transparency principles. Information Commissioner’s Office. http://www.ico.gov.uk/for_organisations/guidance_index/~/media/documents/library/Data_Protection/Detailed_specialist_guides/crime_mapping.ashx

  • Khan, B. K., Strong, D. M., & Yang, R. Y. (2002). Information quality benchmarks: Product and service performance. Communications of the ACM, 45(4), 184–192.

    Article  Google Scholar 

  • Lenat, D., & Guha, R. V. (1990). Building large knowledge based systems: Representation and inference in the CYC project. Reading: Addison-Wesley.

    Google Scholar 

  • Manyika, J., et al. (2011). Big data: The next frontier for innovation, competition and productivity. Washington, DC: McKinsey Global Institute.

    Google Scholar 

  • Murray-Rust, P. (2008). Open data in science. Serials Review, 34(1), 52–64.

    Article  Google Scholar 

  • O’Hara, K. (2011). Transparent government, not transparent citizens: A report on privacy and transparency for the Cabinet Office. Cabinet Office. http://www.cabinetoffice.gov.uk/resource-library/independent-transparency-and-privacy-review

  • O’Hara, K. (2012a). Data quality, government data and the open data infosphere. In AISB/IACAP world congress 2012: Information quality symposium. Birmingham: The Society for the Study of Artificial Intelligence and Simulation of Behaviour. http://eprints.soton.ac.uk/340045/

  • O’Hara, K. (2012b). Transparency, open data and trust in government: Shaping the infosphere. In ACM conference on Web Science (WebSci2012) (pp. 223–232). Evanston: ACM, New York.

    Google Scholar 

  • Shadbolt, N., & O’Hara, K. (2013). Linked data in government. IEEE Internet Computing, 17(4), 72–77.

    Article  Google Scholar 

  • Shadbolt, N., Berners-Lee, T., & Hall, W. (2006). The semantic web revisited. IEEE Intelligent Systems, 21(3), 96–101.

    Article  Google Scholar 

  • Shadbolt, N., O’Hara, K., Berners-Lee, T., Gibbins, N., Glaser, H., Hall, W., & schraefel, m. c. (2012). Linked open government data: Lessons from data.gov.uk. IEEE Intelligent Systems, 27(3), 16–24.

    Article  Google Scholar 

  • Tullo, C. (2011). Online access to UK legislation: strategy and structure. In M. A. Biasiotti & S. Faro (Eds.), From information to knowledge (Frontiers in artificial intelligence and applications, Vol. 236, pp. 21–32). Amsterdam: Ios Press.

    Google Scholar 

  • Wind-Cowie, M., & Lekhi, R. (2012). The data dividend. London: Demos.

    Google Scholar 

Download references

Acknowledgements

This work is supported by SOCIAM: The Theory and Practice of Social Machines, funded by the UK Engineering and Physical Sciences Research Council (EPSRC) under grant number EP/J017728/1. Thanks are owing to audiences at a number of talks and conferences, including the Information Quality Symposium at the AISB/IACAP World Congress 2012, Birmingham, July 2012.

Author information

Authors and Affiliations

  1. Electronics and Computer Science, University of Southampton, Highfield, Southampton, SO17 1BJ, UK

    Kieron O’Hara

Authors
  1. Kieron O’Hara
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kieron O’Hara .

Editor information

Editors and Affiliations

  1. Oxford Internet Institute, University of Oxford, Oxford, Oxfordshire, UK

    Luciano Floridi

  2. Department of Science and Technology Studies, University College London, London, UK

    Phyllis Illari

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this chapter

Cite this chapter

O’Hara, K. (2014). Enhancing the Quality of Open Data. In: Floridi, L., Illari, P. (eds) The Philosophy of Information Quality. Synthese Library, vol 358. Springer, Cham. https://doi.org/10.1007/978-3-319-07121-3_11

Download citation

Publish with us

Policies and ethics

Search

Navigation